Many fields dealing with research or other endeavors require the use and manipulation of huge data arrays. All fields that need to solve and predict problems and solutions need methods of handling large data arrays. Current methods of dealing with large data arrays are inadequate to properly consider and integrate data from the real world.
Past and present machines are deficient because the software for these processes is sequential. Sequential processes are not able to handle the huge data arrays of randomness found in the real world. Additionally, current machines are not able to communicate with one another in order to upgrade information.
Current machines are also not able to solve problems or predict problems and solutions in tiered structures.
Needs exist for improved methods for integrating data into large data arrays and predicting and solving problems using these data arrays.